Explainable AI in Health Informatics by Rajanikanth Aluvalu (.PDF)+

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File Size: 38.9 MB

Explainable AI in Health Informatics by Rajanikanth Aluvalu, Mayuri Mehta, Patrick Siarry
Requirements: .ePUB, .PDF reader, 38.9 MB
Overview: This book provides a comprehensive review of the latest research in the area of Explainable Artificial Intelligence (XAI) in health informatics. It focuses on how explainable AI models can work together with humans to assist them in decision-making, leading to improved diagnosis and prognosis in healthcare. This book includes a collection of techniques and systems of XAI in health informatics and gives a wider perspective about the impact created by them. The book covers the different aspects, such as robotics, informatics, drugs, patients, etc., related to XAI in healthcare. The book is suitable for both beginners and advanced AI practitioners, including students, academicians, researchers, and industry professionals. It serves as an excellent reference for undergraduate and graduate-level courses on AI for medicine/healthcare or XAI for medicine/healthcare. Medical institutions can also utilize this book as reference material and provide tutorials to medical professionals on how the XAI techniques can contribute to trustworthy diagnosis and prediction of the diseases. This book is a collection of 12 chapters that provide an overview of recent advances in this area, that is, how Explainable Artificial Intelligence techniques help provide trustworthy solutions in healthcare.
Genre: Non-Fiction > Tech & Devices

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